Podcasts about Beam

Beam and Austin Ward on a Monday Night. Warde Manuel is out as AD of Michigan. The Buckeyes pick up another big commitment. Changes at the Schott. It's a Three Thoughts Tues....Monday..... And SEC and ACC coaches say silly things

Our immediate reactions right after the meet!   Everything from the 2026 U.S. Classic, including Reese Esponda's all-around victory, Katelyn Ohashi's return to elite competition, Skye Blakely's event titles, Jade Carey's upgrades, Nationals qualification, the biggest breakout performances, and historic gay TV moment.  We also discuss NBC's broadcast, routine construction, Nationals qualifying procedures, and answer Club Gym Nerd questions. This is our live Q&A show, where we answer your questions. Here's how to ask questions live. Can't make it live? Add Club bonus episodes to your favorite podcast player (instructions here). For the extended episode  log in, refresh this page and the extended player for Club Members will appear below. Not a member? Join here. CHAPTERS 00:00 – Historic Moment in Gay Gymnastics History 01:31 – Jade Carey Takes the Long View 03:11 – Reese Esponda's Bars, Beam and Winning Floor 05:41 – Katelyn Ohashi's Successful Elite Return 06:23 – Ohashi's Beam Inquiry and Qualification Score 08:45 – The Meet's Real Winner: Smart Routine Construction 10:09 – Why Ohashi's Comeback Is Already a Huge Success 13:07 – Could Ohashi Be Invited to Nationals? 15:53 – Skye Blakely Wins Bars and Beam 16:42 – Ally Damelio's Seitz 17:20 – Were the U.S. Classic Scores Too Generous? 19:12 – Leanne Wong's Smarter Beam Composition 22:53 – BONUS FOR CLUB MEMBERS BEGINS To listen to the full episode login or join Club Gym Nerd for the extended Behind The Scenes episode every Friday: https://gymcastic.com/club/ 23:53 – Why Katelyn Ohashi and Laurie Hernandez + Jade Made Jessica Cry 26:48 – Breakout Stars: Zoey Molomo and Isabella Anzola 31:50 – Building a World Team From the U.S. Classic 33:31 – How to Watch Peacock and the International Feed Together 34:29 – Jade Carey's Full-Twisting Double Layout Technique 36:50 – Do World Team Members Have to Be Top-Five All-Arounders? 37:10 – Should Jade Carey Increase Her Bars Difficulty? 42:02 – Charleigh Bullock's Compelling Bars Score 42:28 – Izzy Stassi's Elite Potential at Oklahoma 44:30 – Is the U.S. Currently a World-Gold Team? 45:32 – Tom Forster and the Selection Committee 49:10 – Why USAG Needs a Single-Event Qualifying Score 51:02 – Suni Lee and the Case for Specialist Qualification 52:25 – Should Katelyn Ohashi Petition to Nationals? 1:00:35 – Gymnasts Still Planning Elite Comebacks 1:03:12 – Shilese Jones' Comeback Status 1:03:30 – The Broadcast's Skye Blakely Resilience Narrative 1:08:48 – The Absurdity of Mandatory "Dry Seasons" 1:09:49 – What Does "No Partying" Actually Mean? 1:10:14 – Jessica Disappears to Dance in the Street 1:10:57 – Is LSU's Injury Management a Problem? SUPPORT OUR WORK Club Gym Nerd: Join Club Gym Nerd for weekly Behind the Scenes episodes, our complete members-only archive, games, the forum and live-show discounts. Shop GymCastic: Shop merch. GYMCASTIC TOOLS, GAMES AND RESOURCES GymCastic tools: LA 2028 Roster Lab, Elite Score Explorer and the International Gymnastics Calendar GymCastic Games GymCastic Newsletters The Balance Beam Situation: Spencer's GIF Code of Points Gymnastics History: Gymnastics history and Code of Points archive from Uncle Tim Resistance Resources  

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

Recorded immediately after Senior Women's podium training at the U.S. Classic. Suni Lee officially announced her comeback documentary, Katelyn Ohashi unveiled upgrades ahead of the U.S. Classic, Jade Carey looked every bit the World Team favorite, and Spencer and Jessica break down everything they saw during senior women's podium training. Plus: behind-the-scenes stories, hot mic moments, start values, fantasy picks, and an extended Club Gym Nerd Q&A.  For the full episode login or join Club Gym Nerd. Here's how to ask questions live. Can't make it live? Add Club bonus episodes to your favorite podcast player (instructions here). Not a member? Join here. Before competition begins, build your team for the 2026 U.S. Classic Fantasy Game. Lineups lock Saturday at 6:45 p.m. Eastern. CHAPTERS 00:00 Welcome, Hot Mics & US Classic Podium Training 00:52 Suni Lee Officially Announces Her Comeback 03:08 Should Single Event Specialists Have a Pathway to Championships? 06:28 Katelyn Ohashi's Upgraded Floor Routine 10:00 Katelyn Ohashi's Beam Changes & Strategy 14:00 Lost Luggage, AARP & Elite Warm-Up Rituals 15:10 Skye Blakely's Beam Upgrade 17:22 Leanne Wong's New Beam Composition 21:15 Beam Connection Bonus Explained 21:56 More Leanne Wong Routine Nerding 23:01 Fantasy Game, Elite Score Explorer & Roster Lab Updates 24:55 Store Sale, Referral Program & Bluesky Groups BONUS FOR CLUB MEMBERS BEGINS To listen to the full episode login or join Club Gym Nerd for the extended Behind The Scenes episode every Friday: https://gymcastic.com/club/ 25:00 Beam Bonus Bungle Story 26:28 Final Thoughts on Leanne's Beam 28:59 Jade Carey Wins Podium Training 30:02 Jade's Upgrades & Event-by-Event Review 31:55 Izzy Stasi's Oklahoma Era & New Choreography 34:10 Zoe Molomo, Simone Rose & Dulcy Caylor Notes 36:45 Comedy Awards, Hot Mic Moments & Withdrawals 37:08 Club Gym Nerd Q&A Begins 38:00 Single-Event Qualification to Nationals Debate 43:02 Should Nationals Matter More Than Worlds Selection? 50:58 Who Was Terrible at Compulsories? 53:31 The Most Memorable Compulsory Disasters 56:40 Are Olympic Comebacks About Passion or Business? 01:01:39 Spencer's Dream Suni Lee Bars Routine 01:05:08 The Perfect Acting Role for Laurie Hernandez 01:05:58 Is Elite Gymnastics Inherently Bad for Kids? 01:08:43 Can You Reach Elite Without Early Specialization? SUPPORT OUR WORK Club Gym Nerd: Join Club Gym Nerd for weekly Behind the Scenes episodes, our complete members-only archive, games, the forum and live-show discounts. Shop GymCastic: Shop merch. GYMCASTIC TOOLS, GAMES AND RESOURCES GymCastic tools: LA 2028 Roster Lab, Elite Score Explorer and the International Gymnastics Calendar GymCastic Games GymCastic Newsletters The Balance Beam Situation: Spencer's GIF Code of Points Gymnastics History: Gymnastics history and Code of Points archive from Uncle Tim Resistance Resources    

This podcast is made possible by our listeners and viewers. If this show has brought you value, you can support it by becoming a member of The Way Forward, our platform designed to help you find the health and freedom community (people, practitioners, schools, farms, and more) near you. Your membership directly supports the podcast and the work we do.The global reset is coming, and we need to get prepared.Gregg Braden is a five-time New York Times best-selling author, scientist, and pioneer in the emerging paradigm bridging science, social policy, and human potential.From 1979 to 1991, Gregg worked as a problem solver during times of crisis for Fortune 500 companies, including Martin Marietta (now Lockheed Martin) where he worked as a Senior Computer Systems Designer, and Cisco Systems, where he became the first Technical Operations Manager in 1991.He continues problem-solving today, and his research resulted in the 2003 discovery of intelligent information coded into the human genome and the 2010 application of fractal time to predict future occurrences of past events.Gregg's work has led to 18 film credits, 13 award-winning books now published in over 40 languages, and he was a 2020 nominee for the prestigious Templeton Prize established by Sir John Templeton to honor “outstanding individuals who have devoted their talents to expanding our vision of human purpose and ultimate reality.”He has presented his discoveries in 34 countries on six continents, and has been invited to speak to the United Nations, Fortune 500 companies, and the U.S. military. His newest book, Pure Human, is a direct response to what he sees as a narrowing window to protect what makes us human before it gets outsourced to computer chips, nano sensors, and brain computer interfaces.Our conversation covers the science of DNA as a fractal antenna, why merging with tech is devolution and not evolution, and the alignment ancient artifacts pointed toward the late 2029 to 2030 window.Gregg also opens up about the Knights Templar roots of American sovereignty, the disclosure hearings, and why localized community is the middle ground most people will end up choosing.If you sense the reset is real but haven't found language for what's actually being reset, start here.You'll Learn:[0:00] Introduction[7:48] How the Knights Templar, the Magna Carta, and Freemasons shaped America's founding[19:41] Ancient tablets, a 2030 planetary alignment, and the tech-merger agenda all point to the same reset window[31:04] Your DNA functions as a fractal antenna tuned to divinity[43:25] Why the human body already outperforms computer chips [53:57] What John Mack's abductee research revealed about our future timeline[1:02:22] Information silos are weaponising the differences at your own dinner table[1:09:08] Localised living emerges as the middle ground between all-in tech and total rejection[1:16:16] The six corporations pushing the technocracy and what disclosure really threatensFind more from Gregg:Gregg Braden | WebsiteFind more from Alec:Alec Zeck | Instagram | XThe Way Forward | InstagramDonate to The Way Forward here.The Way Forward is Sponsored By:Want more crypto insights and a community to back you up?Join the Crypto Freedom Academy today. It's 100% free and designed to help you master the markets.

Imagine a dark warehouse. Racks and racks of devices with wires, tubes, and electronics sticking out. The next AI data center? No. This is Lila Sciences‘ dream for the future of science. A dark warehouse full of AI-guided robotics and lab equipment, cranking out new experiments 24/7, building toward a scientific superintelligence.Their automated lab is almost hypnotizing to watch. They have floating plates zipping around on Wall-E-esque tracks, used vision-language models to control Windows 95 boxes, and created the world's largest collection of voided warranties. In the process they've built a massive library of scientific reasoning tokens. Over 10 trillion of them, all experimentally validated.No warranties were voided in the making of this videoTo say Lila is ambitious is an understatement. Their goal is a scientific superintelligence wired directly into the wet lab. They are all in on the bitter lesson, and the thesis follows from it: a lab is an infinite token generator. Produce data at scale, and the synergies give you a general reasoner that can tackle any scientific problem. They are committing hard. Biology, chemistry, drug discovery, and materials science, all at the same time. Time will tell if it works, but it is an exciting hypothesis.In our latest episode we sat down with Lila's very own Andy Beam (CTO) and Rafa Gómez-Bombarelli (CSO, physical sciences) and went on a journey through the possibilities of AI-run science, almost as wide-ranging as Lila's goals.Did we mention they do both materials science and biology? In the same AI science factory? Same time, same lab, same AI. Finally a guest who can settle a long-running debate we've had amongst ourselves: is biology or materials science harder?Watch to find out!We discuss:* The internet is spent, science is next. Why Lila thinks the scientific method is the last untapped internet-scale dataset, and why they treat RL as a data generation mechanism with nature as the verifier.* The lab as a data center. Instruments as nodes on a graph, a magnetically levitating “PCI bus” transport layer between them, orchestration as a slurm queue. Andy is not short on analogies.* Why Lila insists it is not an automation company. They optimize for flexibility and generalizability over raw throughput, which means humans stay below the API line wherever automating does not pay.* Your experiment has a runtime. We put Escalante Bio's question to Andy: if science is the token generator, what is the runtime of your data collection? His answer, in short, is that you cannot make the ribosome go faster. Why Lila bets on fast round-over-round iteration rather than big noisy multiplexed screens, and how Rafa's team rebuilt a gas sorption measurement to run roughly 2,500x faster.* What is actually in 10 trillion scientific tokens. Not sequences. Experimentally verified reasoning traces, a kind of data that Andy argues exists on the internet in quantities that round to zero.* Breadth as a path to depth. Small molecule chemistry priors transferring to metal organic frameworks for carbon capture, and the claim that the general model beats domain-specific models sample for sample.* If you have the data, what do you need the model for? Sri Kosuri's koan about the ML-for-drug-discovery business model, and Andy's answer: the coding model got better because it also read Shakespeare and carnitas recipes.* The serendipity they want to automate. Emily Whitehead survived the first pediatric CAR-T cure only because the doctor treating her happened to know, from pediatric arthritis, which antibody would blunt her IL-6 response. Roll that dice again and you probably lose her. Breadth is how you stop depending on luck.* Move 37 for catalysts. Model suggestions for platinum-group-free electrocatalysts that went from boring, to what a 40-paper expert called stupid, to the best performers they have made.* Six months to in vivo CAR-T data in non-human primates, and the zero-FTE virtual startup commercial model that fell out of it. For context on why that number is startling, AbbVie paid $2.1B for Capstan on the strength of preclinical in vivo CAR-T data.* You cannot have scientific superintelligence if you are just a good test taker. Ken Stanley, who wrote Why Greatness Cannot Be Planned, runs open-endedness at Lila. RL at scale gives you a ruthlessly Vulcan problem solver. Machine creativity is a different thing, and it is the part nobody has solved.* The chain of thought is an unreliable narrator. The model reasons in latent space and only emits tokens. Sometimes it skips the experiment entirely and is still right. So how much do you trust the reasoning versus the verifier?* Reward hacking when the rollout is physical. Chains of thought that collapse into repetition, and a model that got annoyed and swore at the scientist who kept asking it to redo a plate map. What happens when a pathological loop has a wet lab inside it?* The bittersweet lesson. Rafa's inversion of the bitter lesson: in AI, scaling is a roadmap. In materials, scaling is a filter, because only the things that scale end up mattering.* Not your typical Flagship company. Why a famously single-asset biotech incubator spun out a platform bet, and Andy's line that if Lila called itself a biopharma it would have a top-three GPU cluster.* Bottlenecks they would remove by fiat. Sim-to-real for physics-based simulation, and the fact that RL training runs at roughly 5% mean FLOP utilization.Watch on YouTube: This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

In this episode of Elixir Wizards, Charles Suggs and Emma Whamond are joined by Zach Daniel, creator of the Ash Framework and Igniter, VP of Engineering at Remedy Meds, and upcoming ElixirConf keynote speaker, to talk about what sits between an LLM and useful engineering work. Zach reflects on how much has changed since his last appearance on the podcast in October 2024, moving from Igniter, code generation, and project patching into AI agents, context layers, and custom engineering workflows. The conversation explores how deterministic tools and probabilistic LLMs can work together, and why the most useful AI systems often depend on the structure built around the model. We also discuss why teams should be careful about outsourcing the systems that hold their organizational knowledge and decision-making. He shares his perspective on owning the AI stack, building internal knowledge systems, training junior developers in an AI-augmented world, avoiding vendor lock-in, and why Elixir may be especially well-suited for safer agentic workflows. Zach will be a keynote speaker at ElixirConf 2026, September 10–11 in Chicago, and the Elixir Wizards will be there too! Join us and the broader Elixir community, and use promo code Elixirwizards for 10% off in-person or virtual tickets at https://elixirconf.com/ Key topics discussed in this episode: Zach Daniel's work with Ash, Igniter, and AI tooling How software development has changed since 2024 Deterministic code generation vs. LLM-generated code Combining structured tools with AI agents What it means to own your AI stack Organizational knowledge as an engineering “spinal column” Context layers, documentation, and internal workflows Building custom agentic systems Security, vendor lock-in, and open source LLMs Junior developers and apprenticeship in the AI era Why Elixir and the BEAM fit agentic workflows Links mentioned: Ash Framework https://ash-hq.org/ Igniter https://igniter.hexdocs.pm/ Phoenix Framework https://www.phoenixframework.org/ Remedy Meds https://remedymeds.com/ Keynote: Code Generators are Dead. Long Live Code Generators - Chris McCord | ElixirConf EU 2025 https://www.youtube.com/watch?v=ojL_VHc4gLk https://phoenix.hexdocs.pm/Mix.Tasks.Phx.Gen.Live.html LSP https://en.wikipedia.org/wiki/Language_Server_Protocol Claude Code https://claude.com/product/claude-code GitHub Actions https://github.com/features/actions Harness Engineering https://en.wikipedia.org/wiki/Agent_harness
Claude SDK https://code.claude.com/docs/en/agent-sdk/overview Zach's Twitter https://x.com/ZachSDaniel1 ElixirConf https://elixirconf.com/ AshConf https://luma.com/wz4z0iz6 Goatmire https://goatmire.com/Special Guest: Zach Daniel.

Tu rêves de lire ton premier livre en français... mais tu ne sais pas par où commencer ? Tu as peur de choisir un livre trop difficile, d'abandonner après quelques pages ou de passer ton temps dans le dictionnaire ?Dans cet épisode, je célèbre le premier anniversaire de mon Book Club, Le Salon de Yasmine. Depuis un an, une vingtaine d'apprenants lisent un livre francophone chaque mois, débattent, se contredisent, découvrent de nouveaux auteurs... et surtout vivent enfin le français autrement.Mais cet épisode est bien plus qu'un anniversaire.Je te partage tout ce que j'aurais aimé savoir avant de lire mon premier livre dans une langue étrangère. Quel niveau faut-il réellement avoir ? Faut-il connaître le passé simple ? Dois-tu chercher tous les mots dans le dictionnaire ? Est-ce grave d'abandonner un livre que tu n'aimes pas ? Les classiques sont-ils vraiment incontournables ?Je démonte aussi plusieurs idées reçues sur la lecture en français et je t'explique pourquoi terminer ton premier livre est probablement l'une des plus grandes étapes de ton apprentissage.Que tu sois un immense lecteur ou quelqu'un qui pense détester les livres, cet épisode risque bien de changer ta manière d'aborder la lecture en français.Et qui sait... peut-être qu'à la fin, tu auras enfin envie d'ouvrir ce premier livre que tu repousses depuis des années.“Le Français avec Yasmine” existe grâce au soutien des membres et élèves payants. Il y a 3 manières de soutenir ce podcast pour qu'il continue à être libre, indépendant et rebelle : 1️⃣ Le Club de Yasmine Le Club privé du podcast qui donne accès à toutes les transcriptions des épisodes relues et corrigées au format PDF, aux épisodes secrets, la newsletter privée en français et l'accès à la communauté des élèves et membres sur Discord pour continuer à partager et se rencontrer. https://lefrancaisavecyasmine.com/club 2️⃣ Les livres du podcast Les transcriptions du podcast sont disponibles dans les livres “Le français avec Yasmine” sur Amazon : http://amazon.com/author/yasminelesire 3️⃣ Les cours de français avec YasminePour aller encore plus loin et améliorer ton français avec moi, je te donne rendez-vous dans mes cours et mes formations digitales. Je donne des cours particuliers (en ligne et à Paris) et des cours en groupe en ligne. Rendez-vous sur le site de mon école pour découvrir le catalogue des cours disponibles : www.ilearnfrench.eu ➡️ Rendez-vous sur les réseaux sociaux Instagram : https://www.instagram.com/ilearnfrench/LinkedIn : https://www.linkedin.com/in/yasmine-lesire-ilearnfrench/ ➡️ Crédit musique La musique de cet épisode est créée par le groupe Beam. Merci à Maayan Smith et son groupe pour la musique.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Pastor Travis begins a new series about rightly dealing with conflict, starting with allowing God to deal with ourselves first.

Welcome back to the Bourbon Road Bar, where Jim and Todd settle in for a five-bottle session packed with limited releases, aged expressions, and a little bit of everything the whiskey world has to offer right now. Tonight's lineup spans wheat whiskey, high-rye bourbon, east-coast rye, and some serious Beam family heavy-hitters — all barrel strength, all worthy of serious attention. On the Tasting Mat: - Makers Mark Star Hill Farms Wheat Whiskey 2026: A 116.4-proof wheat whiskey bottled at 700ml, featuring a revised mash bill of 62% malted wheat, 27% wheat, and 11% malted barley — including undisclosed amounts of hard red and hard white wheat, plus experimental barrels pulled from three warehouses with a 20-point proof swing. Aged 7–8 years. The nose opens with earthy cherry, turkey figs, and dark fruit, while the palate delivers an oily, velvety texture with baking spices, vanilla, and a distinctive wheat whiskey bite on the back of the palate. MSRP $100. *(00:01:48)* - New Riff 10 Year Bourbon 2026: Bottled at 116.9 proof from a mash bill of 65% corn, 30% rye, and 5% malted barley, this Kentucky bourbon offers a nose of caramel, vanilla, and baking spices with a hint of root beer. On the palate, a honeyed peach and dried apricot character emerges alongside tobacco, leather, and mature oak — drying toward the finish with impressive length. Available at New Riff Distillery and to whiskey club members. MSRP $89.99. *(00:09:50)* - New Riff 10 Year Rye 2026: A 95% rye, 5% malted barley mash bill bottled at 118.8 proof, this east-coast rye comes in at the same price point of $89.99. The nose is immediately striking — spearmint, pine forest, citrus zest, and dried orange. The palate is exceptionally thick and viscous, carrying the mint and zest through with clove, pine nut, and a cooling quality that gives way to a long, peppery oak finish. Available at New Riff Distillery and to whiskey club members. *(00:17:00)* - Little Book Chapter 10 "All the Wiser" 2026: Freddie Noe's tenth Little Book chapter is an homage to the beloved Chapter 3 "The Road Home," blending 11-year Knob Creek, 14-year Basil Hayden, 10-year Booker's, 9-year Baker's, and a 4-year Jim Beam finished in sherry and toasted casks — all uncut at 122.6 proof. The nose is rich and mahogany-dark with vanilla, nuttiness, and a subtle sherry influence. The palate is decadent: dark Luxardo cherry, chocolate, snicker-like nuttiness, molasses, and a long, spicy, sizzling finish that simply refuses to leave. MSRP $160 for 750ml. *(00:27:17)* - Booker's 2026-01 "Big Easy Batch": The first Booker's batch of 2026, named in honor of Booker Noe's legendary love of New Orleans, is aged 7 years, 2 months, and 15 days at a big 129.1 proof. Mash bill is 77% corn, 13% rye, and 10% malted barley. The nose presents caramel apple, green apple, and pie crust. On the palate, a perfectly cooked caramel apple pie character develops with a noticeable fruitiness that runs a bit off the typical Booker's nutty profile — finishing with warmth and spice. MSRP $100 for 750ml. *(00:37:14)* Five barrel-strength pours, two distilleries, and one very tough call at the end — this is the kind of evening that makes the Bourbon Road Bar worth pulling up a stool for. Whether you're hunting shelf staples or chasing limited releases, tonight's lineup has something to put on your radar. As always, check out the full tasting notes and scores over at TheBourbon Road.com, and we'll see you down the Bourbon Road.

Beam and Justin Zwick on a Wednesday spectacular. How close is Jeremiah Smith to the Triple Crown at Ohio State? What are the projections for Ohio State's season? Is there a fanbase crazier than OSU? Plus, Austin Ward drops by!

Tout le monde connaît les gaufres.Mais est-ce que tu connais vraiment leur histoire ?Dans cet épisode, je t'emmène en Belgique, un pays qui occupe une place très particulière dans mon cœur, pour découvrir l'une de ses spécialités les plus célèbres.Enfin... ses spécialités.Parce qu'il n'existe pas une seule gaufre belge, mais plusieurs. Et crois-moi, elles n'ont pas grand-chose en commun.Ensemble, nous allons découvrir ce qui distingue la gaufre de Liège de la gaufre de Bruxelles, pourquoi elles sont devenues de véritables symboles de la gastronomie belge et comment elles ont conquis le reste du monde.Mais ce voyage ne s'arrête pas aux frontières de la Belgique.Nous remonterons jusqu'au Moyen Âge, nous parlerons d'histoire, de traditions culinaires, de marketing, puis nous traverserons l'Atlantique pour comprendre comment les célèbres chicken and waffles sont apparus aux États-Unis.Comme souvent, derrière une spécialité que l'on croit connaître se cache une histoire beaucoup plus riche, beaucoup plus surprenante... et parfois totalement inattendue.Si tu aimes découvrir la langue française à travers la culture, l'histoire et la gastronomie, tu vas adorer cet épisode.Et je te préviens : après l'avoir écouté, tu risques d'avoir très, très envie de manger une gaufre... mais surtout, tu ne la regarderas plus jamais de la même manière.“Le Français avec Yasmine” existe grâce au soutien des membres et élèves payants. Il y a 3 manières de soutenir ce podcast pour qu'il continue à être libre, indépendant et rebelle : 1️⃣ Le Club de Yasmine Le Club privé du podcast qui donne accès à toutes les transcriptions des épisodes relues et corrigées au format PDF, aux épisodes secrets par an, la newsletter privée en français et l'accès à la communauté des élèves et membres sur Discord pour continuer à partager et se rencontrer. https://lefrancaisavecyasmine.com/club 2️⃣ Les livres du podcast Les transcriptions du podcast sont disponibles dans les livres “Le français avec Yasmine” sur Amazon : http://amazon.com/author/yasminelesire 3️⃣ Les cours de français avec YasminePour aller encore plus loin et améliorer ton français avec moi, je te donne rendez-vous dans mes cours et mes formations digitales. Je donne des cours particuliers (en ligne et à Paris) et des cours en groupe en ligne. Rendez-vous sur le site de mon école pour découvrir le catalogue des cours disponibles : www.ilearnfrench.eu ➡️ Rendez-vous sur les réseaux sociaux Instagram : https://www.instagram.com/ilearnfrench/LinkedIn : https://www.linkedin.com/in/yasmine-lesire-ilearnfrench/ ➡️ Crédit musique La musique de cet épisode est créée par le groupe Beam. Merci à Maayan Smith et son groupe pour la musique. Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Our body doesn't need minerals the way we think.Caroline Alan, co-founder of BEAM Minerals and author of The Mineral Reset, has spent years studying why our soils, food, and cells have all run dry at the same time.A US Senate document from 1936 warned about mineral depletion in American soil. Almost a century later, nothing's changed, and the studies on nutrient density in modern crops back that up.What I find fascinating is how this connects to energy itself. A fully mineralized body can generate around 1,200 watts of electricity in a day. Most of us aren't anywhere close.Caroline breaks down why pills made from rocks, shells, and bones don't absorb, how plant-based humic and fulvic substances act as nature's pre-formulated delivery system, and why concentrated single minerals can pull calcium and phosphorus out of your bones over time.She also explains the magnet-like way humic molecules bind heavy metals and carry them out of the body.Visit beamminerals.com/luke and use code LUKE20 for 20% off.Register for the live Mineral Reset Program Bookinar at mineralresetbook.com/bookinarYou'll learn:[0:00] Introduction[3:25] The 1936 congressional warning about soil depletion that we've done nothing about[11:51] 90% of rock, shell, and bone-based mineral supplements end up in the toilet[21:52] Fulvic sprayed on mosquito bites stops the itch almost instantly[26:16] Can gray hair actually reverse with mineral replenishment?[33:43] How an entire rainforest got compressed into a two-foot strata of humate[45:05] The Oligoscan reveals what's actually inside your cells, not just what you're excreting[50:01] Heavy metals bound in the humic molecule act as magnets instead of toxins[54:35] The paradox of aluminum in zeolite and lead in humic that actually detoxes you[1:00:05] How to stack MicroBoost and Electrolyze around your sauna sessions[1:03:29] Practitioners now tell chronically ill clients to start with minerals first[1:11:05] Quinton and sea plasma miss the delivery system that makes fulvic uniqueResources Mentioned:Modern Miracle Men by Rex Beach | DocumentChanges in USDA food composition data for 43 garden crops, 1950 to 1999 by Davis et al. | StudyMitolife Radio | PodcastMitolife Panacea Shilajit | WebsiteGraham Hancock | WebsiteThe Oligoscan | WebsiteLiving Silica | WebsiteZeoCharge | WebsiteMitozen Lumetol Blue Bars | WebsiteQuinton Marine Plasma | WebsiteFull show notes at lukestorey.com/minerals3Related The Life Stylist Episodes:Unlock Nature's Nutrition & Detox Codes: Fulvic + Humic Mineral Power w/ BEAM's Caroline Alan | PodcastGet Minerals In & Toxins Out to Power Your Mitochondria, Hormones, & Brain | PodcastWhy Fixing Mineral Balance w/ Hair Testing & Nano Minerals is Priority #1 feat. Barton Scott | PodcastMineral Deficiency and Metal Toxicity: The Perfect Storm and How to Fix It | PodcastDemystifying The Myths & Magic of Zeolite: Detoxing Metals, Mold, & Mycotoxins Safely | PodcastThe Ultimate Water Show! Filter + Alkaline Myths, & The Miracle Sea Water Solution Of The Century W/ Robert Slovak | PodcastFind more from Caroline:Caroline Alan | Website | InstagramBeam Minerals | Website | Instagram | Facebook | X | TikTok | YouTubeRead: The Mineral Reset: An Essential Guide to Replenishing Your Body and Restoring Your Health by Caroline Alan | BookFind more from Luke:Luke Storey | Instagram | Facebook | X | YouTube | LinkedInThe Life Stylist is Brought To You By:JUST THRIVE | Head to justthrivehealth.com/luke and use code LUKE to save 20%. ACTIVE SKIN REPAIR | Visit lukestorey.com/skinrepair and use code LUKE for 20% off your order.NUCALM | Visit lukestorey.com/nucalm to start your free seven-day trial and save 15% on your subscription.QUANTUM UPGRADE | Visit lukestorey.com/quantumupgrade and use code LUKE15 to start your 15-day free trial.

Austin and Beam on a Tuesday night show. What OSU games remind us of the US performance? Birm joins us in studio to talk all things Ohio State. Media days are upon us. And who's gonna get the ball the most this season?

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Immerse yourself in captivating science fiction short stories, delivered daily! Explore futuristic worlds, time travel, alien encounters, and mind-bending adventures. Perfect for sci-fi lovers looking for a quick and engaging listen each day.

For review:1. US-Saudi relations have significantly deteriorated in recent months amid anger in Riyadh over Washington's decision to launch a war against Iran that has caused massive blowback for the rest of the region, to the extent that the US is reportedly considering pulling troops from the Gulf kingdom.2. Funeral processions for Khamenei will begin on Saturday in Tehran and conclude on July 9 with his burial in his hometown of Mashhad, with additional ceremonies planned in Qom and Iraq in between. The ceremonies are expected to draw 15 to 20 million mourners, according to officials, which would make it the biggest state funeral in the country's history.3. Syria's foreign minister said during a visit to Beirut on Thursday that Syria was open to meeting the Iran-backed Lebanese terror group Hezbollah “if interests require it,” Lebanon's state news agency reported.Asaad al-Shaibani met Lebanese government leaders, including President Joseph Aoun and parliament speaker Nabih Berri, a Hezbollah ally. 4. Israel has successfully completed a series of tests on an upgraded version of its Iron Dome aerial defense system, demonstrating new joint operational capabilities with the Iron Beam laser system, the Israeli ministry of defense said on Tuesday. This integration is a prerequisite for future operational deployments allowing commanders to dynamically toggle between missile and laser interceptions based on the nature of the incoming threat, system availability and cost-benefit calculations.5. President Donald Trump will traveled for the first time on the new Air Force One aircraft Wednesday, according to the White House. 

Tony Katz is guest hosting today and we've got Anna Paulina Luna here to discuss the Save Act and uncovering MKUltra. Then we are speaking with William Jacobson to dig into the supreme court rulings from this week! -------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast -------------------- Bedford Reinforced Plastics - https://www.bedfordreinforced.com/spicer -------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER  to receive 40% off your order Learn more about your ad choices. Visit megaphone.fm/adchoices

« Allons enfants de la patrie, le jour de gloire est arrivé… »Tu connais sûrement ces paroles. Mais est-ce que tu les comprends vraiment ?À l'occasion du 14 juillet, la fête nationale française, cet épisode te plonge au cœur de l'hymne national français : La Marseillaise. Un hymne que tout le monde reconnaît, mais que très peu de gens connaissent vraiment.Dans cet épisode, on explore ensemble :➡️D'où vient La Marseillaise et pourquoi elle ne vient pas du tout de Marseille (oui, vraiment)➡️Qui l'a écrite, pourquoi, et dans quel contexte historique un contexte qui ressemble étrangement à certaines situations d'aujourd'hui➡️Ce que les paroles veulent vraiment dire : le vocabulaire, la grammaire, les images, les sous-entendus violents... et les phrases qui font encore polémique en 2026➡️Pourquoi certains Français refusent de la chanter et les débats que ça provoqueCet épisode est aussi une belle occasion de travailler ton vocabulaire historique et politique en français : révolution, citoyens, tyrannie, étendard, patrie… Des mots qu'on n'apprend pas dans les manuels scolaires.La Marseillaise, c'est bien plus qu'un chant. C'est un miroir de la France : fière, passionnée, contradictoire et qui n'a pas fini de faire débattre.Les membres du Club ont accès à la version longue de La Marseillaise ainsi qu'à la discussion en live Q&A.“Le Français avec Yasmine” existe grâce au soutien des membres et élèves payants. 1️⃣ Le Club de Yasmine Le Club privé du podcast qui donne accès à toutes les transcriptions des épisodes, aux épisodes secrets, la newsletter privée en français et l'accès à la communauté des élèves et membres sur Discord pour continuer à partager et se rencontrer. https://lefrancaisavecyasmine.com/club 2️⃣ Les livres du podcast Les transcriptions du podcast sont disponibles dans les livres “Le français avec Yasmine” sur Amazon : http://amazon.com/author/yasminelesire 3️⃣ Les cours de français avec YasminePour aller encore plus loin et améliorer ton français avec moi, je te donne rendez-vous dans mes cours et mes formations digitales. Je donne des cours particuliers (en ligne et à Paris) et des cours en groupe en ligne. Rendez-vous sur le site de mon école pour découvrir le catalogue des cours disponibles : www.ilearnfrench.eu ➡️ Rendez-vous sur les réseaux sociaux Instagram : https://www.instagram.com/ilearnfrench/LinkedIn : https://www.linkedin.com/in/yasmine-lesire-ilearnfrench/ ➡️ Crédit musique La musique de cet épisode est créée par le groupe Beam. Merci à Maayan Smith et son groupe pour la musique. Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Grace Curley guests hosts the show today! We're talking to Jon Fetherson about the fraud in Maine, who's taking the money, where they are taking it and how they are taking your tax dollars. Then we are speaking with Dan Schneider of Media Research Center about AI and it's place in our lives and when to know when to trust it and not trust it. ------------------ https://www.seanspicer.com subscribe for an ad free version of this podcast ------------------ Beam - ⁠⁠https://www.shopbeam.com/SPICER  to receive 40% off your order ------------------ Boll & Branch - https://www.bollandbranch.com/SPICER for 20% OFF and FREE SHIPPING Learn more about your ad choices. Visit megaphone.fm/adchoices

Contributor: Travis Barlock, MD Educational Pearls:   First-pass success is critical to limit complications from apnea, hypoxia, and airway trauma.  Complication rate for patients intubated on the first pass is 14% Complication rates increase to 47% after two attempts, 64% after three, and 71% after the fourth attempt   How to improve likelihood of first-pass success: Use Video laryngoscopy (VL). VL increases chance of first-pass success to 85% from 71% Use a bougie, especially in patients with anatomically difficult or otherwise obstructed airways. The BEAM study cites a success rate in these patients of 96% with a bougie, compared to 82% without Use a Checklist mnemonic (SOAPME) Suction – On, ready, and within reach Oxygen – Patient is preoxygenated Adjuncts – Oral/nasal adjuncts and BVM ready Positioning - Patient positioned properly; consider obesity, using semi-Fowler/head-up positioning Medications – Rapid sequence intubation (RSI), sedation, vasopressor, and other medications prepared as necessary Equipment – Laryngoscope (blade), tube, bougie/stylet, syringe, scalpel/cric kit, others ready as necessary References Sakles, J.C., Chiu, S., Mosier, J., Walker, C. and Stolz, U. (2013), The Importance of First Pass Success When Performing Orotracheal Intubation in the Emergency Department. Acad Emerg Med, 20: 71-78. https://doi.org/10.1111/acem.12055 Prekker ME, Driver BE, Trent SA, et al. Video versus Direct Laryngoscopy for Tracheal Intubation of Critically Ill Adults. New England Journal of Medicine. 2023;389(5). doi:https://doi.org/10.1056/nejmoa2301601 Driver BE, Prekker ME, Klein LR, et al. Effect of Use of a Bougie vs Endotracheal Tube and Stylet on First-Attempt Intubation Success Among Patients With Difficult Airways Undergoing Emergency Intubation: A Randomized Clinical Trial. JAMA. 2018;319(21):2179–2189. doi:10.1001/jama.2018.6496 ‌Turner JS, Bucca AW, Propst SL, et al. Association of Checklist Use in Endotracheal Intubation With Clinically Important Outcomes: A Systematic Review and Meta-analysis. JAMA Netw Open. 2020;3(7):e209278. doi:10.1001/jamanetworkopen.2020.9278 Turner, Joseph S et al. "Feasibility of  upright patient positioning and intubation success rates At two academic EDs." The American journal of emergency medicine vol. 35,7 (2017): 986-992. doi:10.1016/j.ajem.2017.02.011   Summarized by Sam Pahl | Edited by Sam Pahl & Ahmed Abdel-Hafiz, NREMT-P   Donate: https://emergencymedicalminute.org/donate/   Join our mailing list: http://eepurl.com/c9ouHf  

Bourbon history is already full of legends, but the Jim Beam Distillery in Claremont, Kentucky has a set of stories that do not fit on a label. We walk through how the Beam family helps shape American whiskey, why Kentucky's corn and limestone water matter, and how a working distillery becomes the kind of place where routine, pride, and memory can feel almost tangible in the air.Then we step into the haunted claims tied to three key locations on the property. Warehouse D brings reports of disembodied footsteps and whistling from empty upper levels, a half-seen figure climbing the stairs, and a man in overalls appearing between the barrel racks. Warehouse K shifts the tone with employee accounts of a woman in an old formal dress who seems to hover on the upper floors, plus the unnerving detail of a floral perfume scent cutting through the heavy smell of aging bourbon. We also talk about the T. Jeremiah Beam House, now a museum, where people report upstairs footsteps, window sightings, and the sound of sample glasses sliding when no one is there.We ground all of it with context, including the 2019 lightning strike warehouse fire and the strange way real disasters can reshape the folklore of a place. If you love paranormal investigation, Kentucky bourbon history, or ghost stories with specific details you can actually test, this one is for you. Subscribe, share this with a fellow ghost hunter, and leave a review, then tell us: which location would you investigate first?Thank you for listening to the Paranormal Peeps Podcast. Check us out on Facebook Paranormal Peeps Podcast or Coldspot Paranormal Research and on Instagram coldspot_paranormal_researchSupport the show

We have an All Star panel here with us to discuss Zohran Mamdanis big win in New York, Chuck Schumer Hakeem Jeffries possibly on there way out, can we get the save act passed and this weeks winners and losers! ------------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast ------------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER to receive 40% off your order ------------------------- Chapter - Call (978) 746-2315. It's free and takes under 20 minutes ------------------------- https://www.MarketInstitute.org - Check them out today ------------------------- My latest book Trump 2.0: The Revolution That Will Permanently Transform America is available for preorder, just click the link: https://a.co/d/67kKgje -------------------------- Learn more about your ad choices. Visit megaphone.fm/adchoices

Beam and Tim May for an hour on a Friday night. Jeremiah Smith makes history. We'll have some beers (and probably a lot of them) and Buckeyes with Pat Murphy live from the World Cup, and Dylan Tyrer drops by to preview the NHL draft!

We're celebrating America 250, diving into what it's going to take to pass the save act, who is and isn't on board, and a HUGE discussion on our children's online activity and how we can protect them and ourselves. --------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast --------------------- Chapter - Call (978) 746-2315. It's free and takes under 20 minutes  --------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER  to receive 40% off your order --------------------- https://www.MarketInstitute.org - Check them out today Learn more about your ad choices. Visit megaphone.fm/adchoices

Beam is back alongside Tim May on a Thursday night! Bruce heads to H-Town, the Woody needs renovating, and the NCAA makes some rule changes. Plus, what's Tim's big thoughts on this Buckeye Team?

Venture into the shadowy realms of power and secrecy with Already Dead, where hosts Jose Galison (@towergangjose) and Austin Picard (@theatrethugawp) dissect the intricate web of conspiracy, covert operations, and the underlying political machinations that might just be pulling the strings of our society.What to Expect: Live Listener Interaction: Call in to share your theories, ask burning questions, or discuss personal experiences related to the topics at hand. In-Depth Explorations: Each episode focuses on a different conspiracy or hidden aspect of political history, offering a platform to question and analyze what's often left unsaid. Thought-Provoking Guests: We invite individuals with insider knowledge or those who've taken the red pill to discuss topics that range from the fringe to the forefront of conspiracy culture. Critical Analysis of Current Affairs: We don't just report on events; we interpret them through the lens of parapolitics, looking for patterns and hidden agendas.Join Us: Every Tuesday at 9:30 PM ET, dive into the depths of the unknown with us. Subscribe, participate in our live call-ins, and be part of a community that seeks to understand the world beyond the surface narrative.Disclaimer: This podcast thrives on speculation, hypothesis, and the examination of alternative theories. It's meant to provoke thought and encourage personal research. Not all discussed is proven fact, but rather a call to question, explore, and understand.Warning: For those not ready to challenge their worldview, tread carefully. Once you enter the world of Already Dead, you might find that the truth is often already dead to the uninitiated. Welcome aboard, where curiosity is your guide.Please consider supporting our work- Austin's Patreon: https://www.patreon.com/c/TheUnderclassPodcastAustin's Spreaker: https://www.spreaker.com/podcast/the-underclass-podcast--6511540Austin's Rumble: https://rumble.com/user/TheUnderclassPodcastAustin's YouTube: https://www.youtube.com/@TheUnderclassPodcast#AlreadyDead #PeterThielsSecretDialogSociety #OligarchicAccelerationism #SocietalDegeneration #TotalitarianTechnocracy #TechnocraticTakeover #BrazilianBlueBeam #FakeAlienInvasion #DisclosureDistraction #UFOPSYOP #CultureCreation #SocialEngineering #MindWarManipulation #SatanicSpiritualTrap #SuspiciousSuicides #ChrisCornell #ChesterBennington #JohnPodesta #NonprofitMusicForRelief #ClintonFoundationBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-underclass-podcast--6511540/support.

James Blair is here to breakdown the latest updates considering midterms and how much money republicans have to spend, when they are going to spend it, and how they are going to spend it. -------------------------------------------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast -------------------------------------------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER to receive 40% off your order -------------------------------------------------------- Chapter - Call (978) 746-2315. It's free and takes under 20 minutes -------------------------------------------------------- https://www.MarketInstitute.org - Check them out today Learn more about your ad choices. Visit megaphone.fm/adchoices

On ne peut pas parler de culture française sans parler de politique et dans l'épisode privé 283, je partageais avec toi 3 scandales politiques français. Ici, je ne vais pas te parler de dérapages politiques sur Twitter qui ont duré 48 heures. Je vais partager avec toi ce qui a traumatisé, choqué, secoué les Français et ce qui a, par conséquent, fait couler beaucoup d'encre. Je te parle des affaires qui ont détruit des carrières, voire des vies. Celles qui ont changé ou imposé des lois.Celles qui ont profondément modifié la manière dont les Français voient leurs dirigeants.Parce qu'en France, il existe une relation très particulière entre le peuple et le pouvoir.Les Français adorent détester leurs hommes politiques sans exception. On adore les débats politiques en famille et entre amis. En tout cas, la méfiance des Français envers les politiques ne vient pas de nulle part.Comme on dit en français, il n'y a jamais de fumée sans feu. Cette méfiance s'est construite à travers des décennies de scandales, de mensonges, d'affaires financières, de corruption, d'écoutes illégales, de financements occultes, de trahisons, parfois même de morts mystérieuses et beaucoup d'impunité. Certaines affaires sont devenues presque des traumatismes nationaux.D'autres ont créé une immense désillusion. Et certaines continuent encore aujourd'hui à influencer la politique française.Alors pour cette première partie des plus gros scandales politiques français, j'invite tous les membres du Club à me rejoindre dans leur espace-membre.Comme pour l'épisode privé 278 sur les plus grandes affaires criminelles en France, j'ai ajouté des ressources complémentaires comme des épisodes de podcast ou des films. Il y a 3 manières de soutenir ce podcast pour qu'il continue à être libre, indépendant et rebelle : 1️⃣ Le Club de Yasmine Le Club privé du podcast qui donne accès à toutes les transcriptions des épisodes, aux épisodes secrets, la newsletter privée en français et l'accès à la communauté des élèves et membres sur Discord. https://lefrancaisavecyasmine.com/club 2️⃣ Les livres du podcast Les transcriptions du podcast sont disponibles dans les livres “Le français avec Yasmine” sur Amazon : http://amazon.com/author/yasminelesire 3️⃣ Les cours de français avec YasmineRendez-vous sur le site de mon école pour découvrir le catalogue des cours disponibles : www.ilearnfrench.eu ➡️ Les réseaux sociaux Instagram : https://www.instagram.com/ilearnfrench/LinkedIn : https://www.linkedin.com/in/yasmine-lesire-ilearnfrench/ La musique de cet épisode est créée par le groupe Beam. Merci à Maayan Smith et son groupe pour la musique.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Venture into the shadowy realms of power and secrecy with Already Dead, where hosts Jose Galison (@towergangjose) and Austin Picard (@theatrethugawp) dissect the intricate web of conspiracy, covert operations, and the underlying political machinations that might just be pulling the strings of our society.What to Expect:Live Listener Interaction: Call in to share your theories, ask burning questions, or discuss personal experiences related to the topics at hand.In-Depth Explorations: Each episode focuses on a different conspiracy or hidden aspect of political history, offering a platform to question and analyze what's often left unsaid.Thought-Provoking Guests: We invite individuals with insider knowledge or those who've taken the red pill to discuss topics that range from the fringe to the forefront of conspiracy culture.Critical Analysis of Current Affairs: We don't just report on events; we interpret them through the lens of parapolitics, looking for patterns and hidden agendas.Join Us: Every Tuesday at 9:30 PM ET, dive into the depths of the unknown with us. Subscribe, participate in our live call-ins, and be part of a community that seeks to understand the world beyond the surface narrative.Disclaimer: This podcast thrives on speculation, hypothesis, and the examination of alternative theories. It's meant to provoke thought and encourage personal research. Not all discussed is proven fact, but rather a call to question, explore, and understand. Warning: For those not ready to challenge their worldview, tread carefully. Once you enter the world of Already Dead, you might find that the truth is often already dead to the uninitiated. Welcome aboard, where curiosity is your guide.Please consider supporting my work- Patreon- https://www.patreon.com/nowayjose2020Only costs $2/month and will get you access to episodes earlier than the public No Way, Jose! Rumble Channel- https://rumble.com/c/c-3379274 No Way, Jose! YouTube Channel- https://youtube.com/channel/UCzyrpy3eo37eiRTq0cXff0gMy Podcast Host- https://redcircle.com/shows/no-way-joseApple podcasts- https://podcasts.apple.com/us/podcast/no-way-jose/id1546040443Spotify- https://open.spotify.com/show/0xUIH4pZ0tM1UxARxPe6ThStitcher- https://www.stitcher.com/show/no-way-jose-2Amazon Music- https://music.amazon.com/podcasts/41237e28-c365-491c-9a31-2c6ef874d89d/No-Way-JoseGoogle Podcasts- https://www.google.com/podcasts?feed=aHR0cHM6Ly9mZWVkcy5yZWRjaXJjbGUuY29tL2ZkM2JkYTE3LTg2OTEtNDc5Ny05Mzc2LTc1M2ExZTE4NGQ5Yw%3D%3DRadioPublic- https://radiopublic.com/no-way-jose-6p1BAO Vurbl- https://vurbl.com/station/4qHi6pyWP9B/Feel free to contact me at thelibertymovementglobal@gmail.com#AlreadyDead #PeterThielsSecretDialogSociety #OligarchicAccelerationism #SocietalDegeneration #TotalitarianTechnocracy #TechnocraticTakeover #BrazilianBlueBeam #FakeAlienInvasion #DisclosureDistraction #UFOPSYOP #CultureCreation #SocialEngineering #MindWarManipulation #SatanicSpiritualTrap #SuspiciousSuicides #ChrisCornell #ChesterBennington #JohnPodesta #NonprofitMusicForRelief #ClintonFoundation

ADAM KINCAID is here to breakdown the midterms and the fight over redistricting -------------------------------------------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast -------------------------------------------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER to receive 40% off your order -------------------------------------------------------- Chapter - Call (978) 746-2315. It's free and takes under 20 minutes -------------------------------------------------------- https://www.MarketInstitute.org - Check them out today Learn more about your ad choices. Visit megaphone.fm/adchoices

This episode examines the Vice President's recent trip to Switzerland alongside the left's preoccupation with the reflecting pool in Washington. Dan Sullivan of Alaska joins us to breakdown the lefts attempt at gaming the system by running their own Dan Sullivan. We also present critical segments featuring external experts who are shedding light on the Fauci Exposed topic. If you need a concise breakdown of how these specific current events impact the broader political climate, this summary provides the necessary context. -------------------------------------------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast -------------------------------------------------------- Chapter - Call (978) 746-2315. It's free and takes under 20 minutes -------------------------------------------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER to receive 40% off your order -------------------------------------------------------- https://www.MarketInstitute.org - Check them out today Learn more about your ad choices. Visit megaphone.fm/adchoices

Bar Talk (our recommendations):Jessica is watching Hallow Road (2025, dir by Babak Anvari); drinking Oak Aged Watermelon Kolsch by Ommegang.Damien is reading Angel Down by Daniel Kraus; drinking Bondstone Toasted Barrel Bourbon.Ryan is reading There Is No Anti-Memetics Division by QNTM; drinking The Obituary (dry gin martini with an absinthe wash). If you liked this week's story, watch Total Recall (1990; dir. Paul Verhoeven). Heck, watch it even if you didn't like this story. Up next: "The Rose Wall" by Joyce Carol Oates Special thank you to Dr Blake Brandes for our Whiskey and the Weird music!  Like, rate, and follow! Check us out @whiskeyandtheweird on Instagram, Threads & Facebook, and at whiskeyandtheweird.com

What does it actually look like when your family dinner table conversations literally shape the history of American whiskey? Well today we're sitting down with a true legend of Kentucky distilling royalty: 2025 Bourbon Hall of Fame Inductee, Craig Beam. Growing up with a last name that defines the entire category, Craig shares what it was really like sitting at the table listening to his father, Parker Beam, and grandfather, Earl Beam, talk shop about Heaven Hill's fermentation and equipment hurdles while simultaneously working cattle and farming. Craig takes us through his early days of pulling grunt work in vacant rickhouses in 1983, learning the legendary family jug yeast process, and eventually stepping up as Master Distiller. We even get to hear Craig's story about how casual conversations while working the farm led to the birth of Elijah Craig, Evan Williams single barrels, and the iconic Parker's Heritage Collection. A master distiller's job used to mean grain buying, pressure washing, and lab work and not just marketing campaigns but that's why he's here today to give us the details about his exciting next chapter at Jackson Purchase Distillery. Show Notes: Craig growing up listening to Parker and Earl Beam balance Heaven Hill distilling mechanics with western Kentucky farming Craig's journey from sweeping out empty rickhouses in 1983 to mastering the family's secret jug yeast lineage An inside look at how farming conversations birthed legendary labels like Elijah Craig and Parker's Heritage Why historic distilling roles required hands-on labor, from grain buying and lab work to pressure washing warehouses How Craig Beam and Terry Ballard teamed up in 2021 to scale a hidden contract distilling powerhouse Technical insights into how a warmer regional climate impacts early barrel color extraction and aging physics Mapping out Jackson Purchase's experimental library, including wheated mash bills, air-dried staves, and American single malts Learn more about your ad choices. Visit megaphone.fm/adchoices

K.C. Keeler's 2027 recruiting class is starting to round into shape after another successful official visit weekend, and we'll get you caught up on the latest verbal commitments. And on the basketball front, you'll hear our 1-on-1 interview with Christian Beam, the 7-foot-1 transfer center who just might give coach Adam Fisher the interior presence he's been missing in his three previous seasons at Temple.  Intro: 0:00 – 9:45 Temple is up to 13 2027 football verbal commits: 9:45 – 13:45 Christian Beam joins the show: 13:45 – 36:52 Mailbag: 36:52 – end

In this episode of Elixir Wizards, Charles Suggs and Emma Whamond are joined by Mike Ratliff, co-founder and CTO of GridVar, to talk about the role software plays in the changing energy infrastructure. With over 30 years of experience in technology, Mike shares the path that took him from the early internet and cloud computing into energy and utility software, along with what he has learned about staying adaptable as the industry continues to shift. Mike explains why building software for the power grid comes with a very different set of constraints than building a typical web application and breaks down some of the challenges utilities are facing, including grid interconnection delays, power quality, increasing energy demand, and the growth of distributed energy resources. We also discuss demand response, microgrids, virtual power plants, battery storage, and how software can help utilities better understand and manage a grid that is becoming more complex. Mike also explains why Elixir and the BEAM are a strong fit for always-on energy systems, how an Erlang MQTT server first led him into the ecosystem, and what it takes to introduce Elixir inside an established organization. The episode closes with a broader look at AI-assisted development, the value of domain expertise, and why technical leaders still need communication, judgment, and a compelling story to move important ideas forward. Key topics discussed in this episode: Mike Ratliff's path from software to energy technology Lessons from three decades of technology industry change The value of generalists in modern software engineering Why good technical judgment remains difficult to replace Building software that interacts with physical infrastructure Why utility technology adoption can move slowly Understanding today's grid interconnection backlog Power quality challenges affecting new grid connections Using simulation to accelerate utility engineering studies Centralized and distributed approaches to grid management How solar energy creates the duck curve Using demand response to balance electricity consumption Edge devices supporting real-time grid coordination Microgrids and resilience in distributed energy systems Cybersecurity considerations for increasingly connected power grids Preparing utility infrastructure for extreme weather events Battery storage and the growth of renewable energy How virtual power plants coordinate distributed resources Why Elixir works well for energy software BEAM reliability for always-on utility infrastructure Discovering Elixir through Erlang and MQTT Building an early virtual power plant with Elixir Making the business case for an Elixir migration Why technical leadership also requires effective storytelling Links Mentioned: GridVAR https://www.gridvar.com/ GridPoint https://www.gridpoint.com/ https://en.wikipedia.org/wiki/2025_Iberian_Peninsula_blackout Demand Response: https://en.wikipedia.org/wiki/Demand_response Virtual Power Plant: https://en.wikipedia.org/wiki/Virtual_power_plant Microgrid: https://en.wikipedia.org/wiki/Microgrid Volts podcast: https://www.volts.wtf/

Chaque année, le 21 juin, des milliers de personnes chantent, dansent et rentrent parfois chez elles au lever du soleil.Et le plus étonnant, c'est que cette tradition que tout le monde connaît est en réalité très récente.Dans cet épisode, tu vas découvrir l'histoire fascinante de la Fête de la musique, un événement créé dans les années 1980 qui est devenu l'une des plus grandes exportations culturelles françaises.Mais derrière les concerts gratuits et l'ambiance festive, se cachent des questions beaucoup plus intéressantes :Pourquoi l'État français a-t-il décidé d'organiser une fête nationale autour de la musique ?Pourquoi le 21 juin a-t-il été choisi ?Pourquoi les Français, qui passent leur temps à se plaindre du bruit, adorent-ils cette immense fête de rue ?Et comment une idée un peu folle imaginée par quelques personnes au ministère de la Culture a-t-elle fini par conquérir plus de 120 pays ?Nous parlerons aussi du rôle de Jack Lang, personnage incontournable mais extrêmement controversé de la vie politique française, ainsi que des critiques qui accompagnent la Fête de la musique depuis sa création.Tu découvriras également pourquoi cet événement raconte beaucoup de choses sur la mentalité française : le rapport à la culture, à l'espace public, à la fête, à l'égalité et même à la contestation.Si tu veux comprendre pourquoi la France entière semble perdre la tête chaque 21 juin, cet épisode est pour toi.“Le Français avec Yasmine” existe grâce au soutien des membres et élèves payants. Il y a 3 manières de soutenir ce podcast pour qu'il continue à être libre, indépendant et rebelle : 1️⃣ Le Club de Yasmine Le Club privé du podcast qui donne accès à toutes les transcriptions des épisodes relues et corrigées au format PDF, à 6 épisodes secrets par an, la newsletter privée en français et l'accès à la communauté des élèves et membres sur Discord pour continuer à partager et se rencontrer. https://lefrancaisavecyasmine.com/club 2️⃣ Les livres du podcast Les transcriptions du podcast sont disponibles dans les livres “Le français avec Yasmine” sur Amazon : http://amazon.com/author/yasminelesire 3️⃣ Les cours de français avec YasminePour aller encore plus loin et améliorer ton français avec moi, je te donne rendez-vous dans mes cours et mes formations digitales. Je donne des cours particuliers (en ligne et à Paris) et des cours en groupe en ligne. Rendez-vous sur le site de mon école pour découvrir le catalogue des cours disponibles : www.ilearnfrench.eu ➡️ Rendez-vous sur les réseaux sociaux Instagram : https://www.instagram.com/ilearnfrench/LinkedIn : https://www.linkedin.com/in/yasmine-lesire-ilearnfrench/ ➡️ Crédit musique La musique de cet épisode est créée par le groupe Beam. Merci à Maayan Smith et son groupe pour la musique. Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Episode 243 of The Hitstreak, a podcast where we talk about anything and everything!  This week we are joined by the Founder of Recruiting Made Simple & Titans Sports Academy, Chance Beam!Episode in a Glance:In this episode of the Hitstreak, I get to welcome a previous guest, Chance Beam, the founder of Recruiting Made Simple, to discuss the complexities of the college recruiting process for athletes. Chance shares his personal journey, including his recent business acquisition and the transformative experiences that led to the creation of his innovative recruiting platform. Our conversation delves into the importance of understanding fit, key performance indicators, and how technology can simplify the recruiting process for both athletes and parents. Chance emphasizes the need for clarity in a landscape filled with overwhelming options and offers insights into how his platform can guide families through the recruiting maze. In this episode, we delve into the complexities of college baseball recruitment, emphasizing the importance of understanding one's starting point in the recruitment process. Finally, we have our rapid-fire questions section, where we talk insights into common myths and misconceptions surrounding recruitment, ultimately encouraging families to focus on the best version of their young athletes.Key Points:- Recruiting Made Simple is a GPS for the recruiting process.- The importance of clarity in the recruiting journey.- Every athlete's journey is unique, like a fingerprint.- Key performance indicators are crucial for college coaches.- Understanding fit is essential for successful recruiting.- Building relationships with coaches is vital for athletes.- Understanding your current level is crucial for aspiring players.- Specialized recruiting services can save time and effort.- Young athletes should focus on personal development.About our guest: Chance Beam is the founder of Recruiting Made Simple (RMS), a data-driven SaaS platform helping baseball and softball families navigate the college recruiting process with greater clarity and confidence. Drawing from nearly two decades of experience and more than 1,200 athlete placements across JUCO, NAIA, and Division I programs, Chance built RMS to simplify recruiting through tools like the Fit Score™, Ask Chance AI, and a database of more than 3,400 college programs — giving families affordable, data-informed guidance without the high cost of traditional recruiting services. Chance is also the founder of Titans Sports Academy (TSA), a Georgia-based player development organization focused on training, team operations, and athlete growth. In addition, he serves on the Cherokee County School Board and brings a systems-driven, accountability-focused mindset to both business and public service. Known for his direct and practical approach, Chance believes development matters more than exposure and that the right information can change an athlete's future.Follow and contact:Instagram: @recruiting_made_simplerecruitingmadesimple.appSubscribe to Nick's top-rated podcast The Hitstreak on Youtube: ⁠https://www.youtube.com/NickHite⁠rFollow and Rate us on Spotify: ⁠https://spotify.com/NickHiter⁠Follow and Rate us on Apple Podcast: ⁠https://podcasts.apple.com/NickHiter⁠Follow and Rate us on iHeartRadio: ⁠https://www.iheart.com/NickHiter

Old Grand-Dad is a titan among budget bourbons, known for its punchy, high-rye mash bill. But the brand is evolving. In this episode, Jake and Scott dive into the deep history of Old Grand-Dad, tracing it from the 1800s through its current era under the Jim Beam umbrella.We explore the expanded lineup, from the standard 7-year bottled-in-bond to ultra-premium, age-stated releases like the rare 16-year. The core of this discussion, however, centers on the beloved 114 proof and the launch of the new signed single barrel variant. Can aging hide the signature OGD profile? Does Beam's extensive line expansion threaten its core brands?We break down tasting notes, discuss warehouse terroir, and offer recommendations for all levels of bourbon explorers navigating this crowded, complex market.

Major James Capers spent years after Vietnam running ambushes behind enemy lines, surviving an assassination attempt in Hamburg, and serving as a bodyguard to President Nixon before a general sent him home after receiving intelligence that his wife and son would be killed on a Saturday morning. But the moment that defines this episode happened after his bloodiest mission — when he was loaded onto a helicopter with his wounded men and his dead dog King, flown through a storm, and placed in a hallway with the bodies. Someone walked by and said this one is dead. Then another person stopped, looked closer, and said this one is breathing. They pulled him out and brought him back to the operating room. In this episode, Major Capers closes out his story — the ambushes, the training mission loss that made him retire, and what he believes about the country he fought for and would fight for again. Support Major James Capers https://www.instagram.com/major_james_capers_jr/ https://www.capersthedoc.com/ https://www.facebook.com/p/Major-James-Capers-Jr-100040737672030/ https://www.pritzkermilitary.org/whats_on/holt-oral-history-program/james-capers-jr-major ---------- SPONSORS PARTICLE FOR MENCheck out Particle's Face Cream here: https://particleformen.co/mikedrop and use my code MIKEDROP for a 20% discount sitewide AMERICAN FINANCING NMLS #182334 nmlsconsumeraccess.org. APR for rates in the 5s start at 6.327% for well qualified borrowers. Call 866-891-3262 for details about credit, costs and terms. Visit https://AmericanFinancing.net/MikeDrop. Average savings based on borrowers who save over $199.99 BETTER HELP Sign up and get 10% off at https://www.betterhelp.com/mikedrop/ BEAM Here's the deal: Beam is giving my listeners the ultimate patriot discount of UP TO 40% off. Try their best‑selling Dream Powder and get UP TO 40% off for a limited time. Go to https://shopbeam.com/products/dream-powder-4?variant=41387075567671&selling_plan=1794441271&utm_source=podcast&utm_medium=sponsorship&utm_campaign=mikedrop&code=applied15&discount=MIKEDROP and use code MIKEDROP at checkout. NAVY SEALS FITNESS APP | HYBRID STRENGTH & CONDITIONING TRAINING Train like a SEAL with Mike Ritland's App. Build real-world strength, endurance and resilience. https://www.coachos-app.com/navy-seals TEAM DOG FOOD, TREATS & SUPPLEMENTS Be Your Dog's Hero: Veteran-owned by a former Navy SEAL and Special Operations K9 Trainer, Team Dog provides a complete diet of science-backed premium dog food, treats, and supplements to optimize your dog's health, forged from rigorous standards and real-world expertise. https://www.teamdog.shop TEAM DOG ONLINE TRAINING Mike Ritland – a former Navy SEAL & Special Operations K9 trainer – shares his simple and effective dog training program to build trust and control with your dog. Based on Mike's bestselling book “Team Dog, Train the Navy SEAL Way”, join tens of thousands of families that successfully trained their way to a better dog. https://www.teamdog.pet SHOP ALL THE MIKE RITLAND BRANDS Get all your Mike Ritland branded gear - Mike Drop | Trikos | Team Dog https://shop.mikeritland.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Steven recently acquired a 1960s bottle of Old Crow. How he got his hands on it is equally as compelling as the bottle itself. So join us this week as we go down the rabbit hole that is dusty bourbon. The bottle we taste on this episode was produced by National Distillers which was a famed producer of whiskey before selling it's entire portfolio to Beam in the 1980s. Since Old Crow is still being produced today, we couldn't resist the urge to compare this old bottle with the current version of the whiskey. A little history, a great story, and sharing a bottle of history was an absolute treat and we are glad you are here for it. --------------------------SocialsIG: https://www.instagram.com/themashupkyFB: https://www.facebook.com/themashupkyYouTube: https://www.youtube.com/@themashupkyJoin our community on Patreon: https://www.patreon.com/TheMashUpBourbonPodcastPartnership(s)Visit Bourbonoutfitter.com and enter code THEMASHUP for a special discount or visit bourbonoutfitter.com/THEMASHUPMusic: All the Fixings by Zachariah HickmanThank you so much for listening!

Admiral Daryl Caudle discusses the future of the Navy and critical warfighting capabilities needed to confront China today. Sean Spicer travels to the Naval War College for an exclusive conversation with Admiral Daryl Caudle. This interview examines the current state of maritime readiness and the strategic adjustments required to maintain superiority in the Pacific theater. If you follow military affairs or defense policy, this discussion provides direct insight into how the Navy warfighting capabilities are evolving to meet modern geopolitical threats. ------------------------------ https://www.seanspicer.com subscribe for an ad free version of this podcast ------------------------------ Chapter - Call (978) 746-2315. It's free and takes under 20 minutes ------------------------------ Beam - ⁠⁠https://www.shopbeam.com/SPICER to receive 40% off your order ------------------------------ https://www.MarketInstitute.org - Check them out today ------------------------------ Learn more about your ad choices. Visit megaphone.fm/adchoices

Major James Capers ran 50 missions in Vietnam as a Force Recon Marine — combat swims in shark-infested waters, a POW rescue that earned him his first Purple Heart and Bronze Star, and a four-day battle that left him wounded with his legs broken and his dog dead. He was one of the few African Americans in Force Recon, and fought his way into Combat Swimmer school when the commanding officer tried to send him home before he even started. He spent three months at Khe Sanh facing a Chinese division, and when the helicopter finally came in on his bloodiest mission, he put every man on board and stayed on the ground alone. President Trump called him personally to invite him to the White House to receive the Medal of Honor. In this episode, Major Capers walks through the missions and what it cost him to bring everybody home. Support Major James Capers https://www.instagram.com/major_james_capers_jr/ https://www.capersthedoc.com/ https://www.facebook.com/p/Major-James-Capers-Jr-100040737672030/ https://www.pritzkermilitary.org/whats_on/holt-oral-history-program/james-capers-jr-major ---------- SPONSORS PARTICLE FOR MENCheck out Particle's Face Cream here: https://particleformen.co/mikedrop and use my code MIKEDROP for a 20% discount sitewide AMERICAN FINANCING NMLS #182334 nmlsconsumeraccess.org. APR for rates in the 5s start at 6.327% for well qualified borrowers. Call 866-891-3262 for details about credit, costs and terms. Visit https://AmericanFinancing.net/MikeDrop. Average savings based on borrowers who save over $199.99 BETTER HELP Sign up and get 10% off at https://www.betterhelp.com/mikedrop/ BEAM Here's the deal: Beam is giving my listeners the ultimate patriot discount of UP TO 40% off. Try their best‑selling Dream Powder and get UP TO 40% off for a limited time. Go to https://shopbeam.com/products/dream-powder-4?variant=41387075567671&selling_plan=1794441271&utm_source=podcast&utm_medium=sponsorship&utm_campaign=mikedrop&code=applied15&discount=MIKEDROP and use code MIKEDROP at checkout. NAVY SEALS FITNESS APP | HYBRID STRENGTH & CONDITIONING TRAINING Train like a SEAL with Mike Ritland's App. Build real-world strength, endurance and resilience. https://www.coachos-app.com/navy-seals TEAM DOG FOOD, TREATS & SUPPLEMENTS Be Your Dog's Hero: Veteran-owned by a former Navy SEAL and Special Operations K9 Trainer, Team Dog provides a complete diet of science-backed premium dog food, treats, and supplements to optimize your dog's health, forged from rigorous standards and real-world expertise. https://www.teamdog.shop TEAM DOG ONLINE TRAINING Mike Ritland – a former Navy SEAL & Special Operations K9 trainer – shares his simple and effective dog training program to build trust and control with your dog. Based on Mike's bestselling book “Team Dog, Train the Navy SEAL Way”, join tens of thousands of families that successfully trained their way to a better dog. https://www.teamdog.pet SHOP ALL THE MIKE RITLAND BRANDS Get all your Mike Ritland branded gear - Mike Drop | Trikos | Team Dog https://shop.mikeritland.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

This episode of the Sean Spicer Show breaks down the newest allegations surrounding the Southern Poverty Law Center and provides context on the latest Supreme Court news affecting the country. Our panel discussion evaluates the implications of these developments for policy and public discourse. We also feature a key segment from a recent congressional hearing where Ms. Wallace-Jones provides testimony. This analysis is designed for viewers who want a clear breakdown of current events and political commentary without the mainstream media filter. You will gain a better understanding of how these legislative and judicial actions intersect. ------------------------------------- https://www.seanspicer.com subscribe for an ad free version of this podcast ------------------------------------- Beam - ⁠⁠https://www.shopbeam.com/SPICER to receive 40% off your order ------------------------------------- Chapter - Call (978) 746-2315. It's free and takes under 20 minutes ------------------------------------- https://www.MarketInstitute.org - Check them out today ------------------------------------- Learn more about your ad choices. Visit megaphone.fm/adchoices

Jim Shannon and Todd Ritter welcome Bill Straub back to the Bourbon Road Bar — aka Jim's basement — for a deep dive into some of the most talked-about new special releases from the industry's biggest players. Bill, the co-founder of Fourgate Whiskey Company and the longtime voice behind ModernThirst.com, brings his seasoned palate and encyclopedic knowledge of mash bills to the table, making for a lively and insightful tasting session across four very different expressions. On the Tasting Mat: - Elijah Craig 15 Year Single Barrel (Barrel #28) — Heaven Hill: Bottled at 108 proof from Heaven Hill's classic 78/12/10 corn-malted barley-rye mash bill, this 15-year expression opens with a distinctive circus peanut and soft marshmallow nose that the guys identify as quintessential Heaven Hill. The palate delivers silky texture with almond and amaretto notes, while a pop of black pepper anchors a long, satisfying finish. MSRP $150. *(00:02:39)* - Old Forester Grand Dad 7 Year Single Barrel — Jim Beam (Old Grand-Dad): At 114 proof and carrying a high-rye mash bill of 63/27/10, this $50 release pours remarkably dark for its age. The nose offers orange marmalade and a subtle citrus-forward brightness, while the palate is smooth and somewhat reserved up front, building into a spicy, rye-bread-toast finish that lingers impressively. *(00:11:47)* - Wild Turkey Austin Nichols Archive Gold Foil Edition (16 Year): The centerpiece of the evening, this 120-proof blend of 16-year barrels from Camp Nelson Rick Houses D, E, and F is the inaugural release in Wild Turkey's new Archive series, designed to evoke the legendary cheesy gold foil bottles of the 1980s and '90s. The nose is rich with leather, graham cracker pie crust, dried fruit, and a compelling dusty vintage quality. On the palate it explodes with sweet tobacco, oak, coffee cake, citrus, and a hint of dark chocolate, delivering wall-to-wall flavor from entry to an extraordinarily long finish. MSRP $400. *(00:26:49)* - Stagg Batch 26A — Buffalo Trace: Coming in at a robust 129.3 proof with no age statement, this barrel-proof release from Buffalo Trace's Mash Bill #1 opens with concentrated brown sugar that lightens and brightens in the glass, revealing cherry cola, grape jelly, and just a touch of citrus. The palate runs straight down the center of the tongue with focused sweetness and a warm, brown-sugar-driven finish. MSRP $65. *(00:36:32)* Four powerhouse releases, four very different price points, and one table of guys who clearly love what they do — this episode is a reminder that the bourbon industry, for all its current turbulence, is still producing some truly extraordinary whiskey. Don't miss Bill's candid thoughts on the state of the market, the cease-and-desist story behind the ModernThirst mash bill table, and why he thinks Heaven Hill's peak window tops out right around 15 years.

Major James Capers led a four day mission in Vietnam that should have killed him. His unit was inserted, took heavy contact, and fought through the night with everything they had. He was wounded, his dog was killed, and when the helicopter finally came in to pull them out, he told the crew to take his men and leave him behind. President Trump signed a bill awarding him the Medal of Honor for what he did on that trail, outnumbered and outgunned, refusing to abandon a single Marine no matter the cost. In this episode, Major Capers sits down to walk through the mission, the decisions made under fire, and what it actually means to bring every man home when everything around you is falling apart. Support Major James Capers https://www.instagram.com/major_james_capers_jr/ https://www.capersthedoc.com/ https://www.facebook.com/p/Major-James-Capers-Jr-100040737672030/ https://www.pritzkermilitary.org/whats_on/holt-oral-history-program/james-capers-jr-major ---------- SPONSORS PARTICLE FOR MENCheck out Particle's Face Cream here: https://particleformen.co/mikedrop and use my code MIKEDROP for a 20% discount sitewide AMERICAN FINANCING NMLS #182334 nmlsconsumeraccess.org. APR for rates in the 5s start at 6.327% for well qualified borrowers. Call 866-891-3262 for details about credit, costs and terms. Visit https://AmericanFinancing.net/MikeDrop. Average savings based on borrowers who save over $199.99 BETTER HELP Sign up and get 10% off at https://www.betterhelp.com/mikedrop/ BEAM Here's the deal: Beam is giving my listeners the ultimate patriot discount of UP TO 40% off. Try their best‑selling Dream Powder and get UP TO 40% off for a limited time. Go to https://shopbeam.com/products/dream-powder-4?variant=41387075567671&selling_plan=1794441271&utm_source=podcast&utm_medium=sponsorship&utm_campaign=mikedrop&code=applied15&discount=MIKEDROP and use code MIKEDROP at checkout. NAVY SEALS FITNESS APP | HYBRID STRENGTH & CONDITIONING TRAINING Train like a SEAL with Mike Ritland's App. Build real-world strength, endurance and resilience. https://www.coachos-app.com/navy-seals TEAM DOG FOOD, TREATS & SUPPLEMENTS Be Your Dog's Hero: Veteran-owned by a former Navy SEAL and Special Operations K9 Trainer, Team Dog provides a complete diet of science-backed premium dog food, treats, and supplements to optimize your dog's health, forged from rigorous standards and real-world expertise. https://www.teamdog.shop TEAM DOG ONLINE TRAINING Mike Ritland – a former Navy SEAL & Special Operations K9 trainer – shares his simple and effective dog training program to build trust and control with your dog. Based on Mike's bestselling book “Team Dog, Train the Navy SEAL Way”, join tens of thousands of families that successfully trained their way to a better dog. https://www.teamdog.pet SHOP ALL THE MIKE RITLAND BRANDS Get all your Mike Ritland branded gear - Mike Drop | Trikos | Team Dog https://shop.mikeritland.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Elite summer is officially here and GymCastic is breaking down the state of the art in gymnastics heading into the 2026 season. We discuss Simone Biles revealing she "almost died," Melanie De Jesus Dos Santos' emotional return to competition in France, and the gymnasts currently setting the global standard on vault, bars, beam and floor. From Kaylia Nemour's historic bars work to Hezly Rivera leading the all-around rankings, we analyze what it actually takes to contend for World medals in 2026. Plus: French Nationals artistry deductions, NCAA news, and the latest gymternet controversies. SUPPORT OUR WORK Club Gym Nerd: Join Here Merch: Shop Now Games  Podcast Tour Tickets Newsletters The Balance Beam Situation: Spencer's GIF Code of Points Gymnastics History and Code of Points Archive from Uncle Tim Resistance Resources SHOW NOTES Simone Biles shared that she "almost died" in what she called one of the scariest experiences of her life. Melanie De Jesus Dos Santos returned to exhibition competition at French Nationals for the first time since the Paris Olympics, performing floor and discussing her recovery and renewal in Martinique. French Nationals introduced separately listed artistry deductions in live scoring — the future is now. Elena Colas won the French all-around title with a 54.250 and continues her rapid rise as one of the top new seniors in the world. We break down the current world leaders on every apparatus and discuss: • Why Kaylia Nemour is redefining bars • Why Hezly Rivera is currently the all-around world leader • What makes beam composition "state of the art" • Why vault scoring may be changing • What separates a 14 floor routine from a 13 in 2026 GYMTERNET NEWS • Utah gymnastics Ghana trip controversy discussion • NCAA age-rule proposal update • New proposed NIL restrictions in Congress • Texas abortion laws and athlete healthcare concerns • Sam Oldham's charity comeback routine • Jackson Harrison Achilles injury • Emma Slevin transfers to Arkansas • Coaching updates across NCAA • Gymnastics Australia concussion investigation CHAPTERS 00:00 Simone Biles' scary health news 01:21 Melanie De Jesus Dos Santos returns at French Nationals 08:30 French Nationals artistry deductions revolution 09:25 Elena Colas wins French Nationals 17:02 Elite Summer 2026 begins 18:08 All-Around World Leaders: Hezly Rivera vs Kaylia Nemour 27:12 Vault world leaders and why vaulting has changed 35:30 Bars: Why Kaylia Nemour is redefining gymnastics 49:05 Beam world leaders and Chinese beam excellence 1:02:02 Floor exercise: what makes a 14 in 2026? 1:10:18 Gymternet News 1:16:04 NCAA age rule proposal explained 1:19:08 New NIL bill and athlete pay debate 1:21:29 Texas abortion laws and athlete safety concerns 1:23:00 Sam Oldham's charity comeback routine 1:24:01 Jackson Harrison injury and Emma Slevin transfer 1:24:33 NCAA rules and laws limiting athlete income 1:25:58 Australia concussion investigation UP NEXT Behind The Scenes Fridays at noon Pacific